Adaptive strategies for route selection en-route in transportation networks

Tak Shing TAI, Chi Ho YEUNG

Research output: Contribution to journalArticlespeer-review

Abstract

We examine adaptive strategies adopted by vehicles for route selection en-route in transportation networks. By studying a model of two-dimensional cellular automata, we model vehicles characterized by a parameter called path-greediness, which corresponds to the tendency for them to travel to their destinations via the shortest path. The path-greediness of each individual vehicle is updated based on the local traffic conditions, to either keep the vehicle travels via a shorter path in an un-congested region or to explore longer diverted paths in a congested region. We found that the optimal number of steps to trigger an update of path-greediness is dependent on the density of vehicles, and the magnitude of path-greediness increment affects the macroscopic traffic conditions of the system. To better coordinate vehicles in denser networks, the update on the tendency for vehicles to travel via the shorter paths should be gradual and less frequent. Copyright © 2021 The Physical Society of the Republic of China (Taiwan). Published by Elsevier B.V. All rights reserved.
Original languageEnglish
JournalChinese Journal of Physics
Early online date12 Aug 2021
DOIs
Publication statusE-pub ahead of print - 12 Aug 2021

Citation

Tai, T. S., & Yeung, C. H. (2021). Adaptive strategies for route selection en-route in transportation networks. Chinese Journal of Physics. Advance online publication. doi: 10.1016/j.cjph.2021.07.024

Keywords

  • Traffic congestion
  • Traffic flow
  • Traffic coordination
  • Cellular automata
  • Adaptive strategies
  • PG student publication

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